1. The Normal Distribution
Chapter 6
The Normal Distribution
Copyright © 2013 The McGraw-Hill Companies, Inc. Permission required for reproduction or display.

2. Copyright © 2012 The McGraw-Hill Companies, Inc.
The Normal Distribution 6
1.1
6-1
Normal Distributions
6-2
Applications of the Normal Distribution
6-3
The Central Limit Theorem
6-4
The Normal Approximation to the Binomial
Distribution
Descriptive and Inferential Statistics
Copyright © 2012 The McGraw-Hill Companies, Inc.
Slide 2

3. 6 The Normal Distribution 1.1 1
Identify distributions as symmetric or skewed. 2
Identify the properties of a normal distribution. 3
Find the area under the standard normal distribution, given various z values. 4
Find probabilities for a normally distributed variable by transforming it into a standard normal variable. 5
Find specific data values for given percentages, using the standard normal distribution.
Descriptive and inferential statistics

4. 6 The Normal Distribution 1.1 6
Use the central limit theorem to solve problems involving sample means for large samples. 7
Use the normal approximation to compute probabilities for a binomial variable.
Descriptive and inferential statistics

5. 6.1 Normal Distributions
Many continuous variables have distributions that are bell-shaped and are called approximately normally distributed variables.
The theoretical curve, called the bell curve or the Gaussian distribution, can be used to study many variables that are not normally distributed but are approximately normal.
Bluman, Chapter 6

6. The mathematical equation for the normal distribution is:
Normal Distributions
The mathematical equation for the normal distribution is:
Bluman, Chapter 6

7. Normal Distributions
The shape and position of the normal distribution curve depend on two parameters, the mean and the standard deviation.
Each normally distributed variable has its own normal distribution curve, which depends on the values of the variable’s mean and standard deviation.
Bluman, Chapter 6

8. Normal Distributions
Bluman, Chapter 6

9. Normal Distribution Properties
The normal distribution curve is bell-shaped.
The mean, median, and mode are equal and located at the center of the distribution.
The normal distribution curve is unimodal (i.e., it has only one mode).
The curve is symmetrical about the mean, which is equivalent to saying that its shape is the same on both sides of a vertical line passing through the center.
Bluman, Chapter 6

10. Normal Distribution Properties
The curve is continuous—i.e., there are no gaps or holes. For each value of X, there is a corresponding value of Y.
The curve never touches the x-axis. Theoretically, no matter how far in either direction the curve extends, it never meets the x-axis—but it gets increasingly closer.
Bluman, Chapter 6

11. Normal Distribution Properties
The total area under the normal distribution curve is equal to 1.00 or 100%.
The area under the normal curve that lies within
one standard deviation of the mean is approximately 0.68 (68%).
two standard deviations of the mean is approximately 0.95 (95%).
three standard deviations of the mean is approximately ( 99.7%).
Bluman, Chapter 6

12. Normal Distribution Properties
Bluman, Chapter 6

13. Standard Normal Distribution
Since each normally distributed variable has its own mean and standard deviation, the shape and location of these curves will vary. In practical applications, one would have to have a table of areas under the curve for each variable. To simplify this, statisticians use the standard normal distribution.
The standard normal distribution is a normal distribution with a mean of 0 and a standard deviation of 1.
Bluman, Chapter 6

14. z value (Standard Value)
The z value is the number of standard deviations that a particular X value is away from the mean. The formula for finding the z value is:
Bluman, Chapter 6

15. Area under the Standard Normal Distribution Curve
1. To the left of any z value:
Look up the z value in the table and use the area given.
Bluman, Chapter 6

16. Area under the Standard Normal Distribution Curve
2. To the right of any z value:
Look up the z value and subtract the area from 1.
Bluman, Chapter 6

17. Area under the Standard Normal Distribution Curve
3. Between two z values:
Look up both z values and subtract the corresponding areas.
Bluman, Chapter 6

18. Chapter 6 Normal Distributions
Section 6-1
Example 6-1
Page #304
Bluman, Chapter 6

19. Example 6-1: Area under the Curve
Find the area to the left of z = 2.06.
The value in the 2.0 row and the 0.06 column of Table E is The area is
Bluman, Chapter 6

20. Chapter 6 Normal Distributions
Section 6-1
Example 6-2
Page #304
Bluman, Chapter 6

21. Example 6-2: Area under the Curve
Find the area to the right of z = –1.19.
The value in the –1.1 row and the .09 column of Table E is The area is 1 – =
Bluman, Chapter 6

22. Chapter 6 Normal Distributions
Section 6-1
Example 6-3
Page #305
Bluman, Chapter 6

23. Example 6-3: Area under the Curve
Find the area between z = and z = –1.37.
The values for z = is and for
z = –1.37 is The area is – =
Bluman, Chapter 6

24. Chapter 6 Normal Distributions
Section 6-1
Example 6-4
Page #306
Bluman, Chapter 6

25. Example 6-4: Probability
a. Find the probability: P(0 < z < 2.32)
The values for z = 2.32 is and for z = 0 is The probability is – =
Bluman, Chapter 6

26. Find the area under the normal distribution curve.
Exercise #7
Find the area under the normal distribution curve.
0.75

27. Exercise #15
0.79
1.28

28. Exercise #31
2.83

29. z Find the z value that corresponds to the given area. 0.8962
Exercise #45
Find the z value that corresponds to the given area.
0.8962 z
– 0.5 =

30. Find the z value that corresponds to the given area.z
0.8962

31. Chapter 6 Normal Distributions
Section 6-1
Example 6-5
Page #307
Bluman, Chapter 6

32. Example 6-5: Probability
Find the z value such that the area under the standard normal distribution curve between 0 and the z value is
Add to to get the cumulative area of Then look for that value inside Table E.
Bluman, Chapter 6

33. Example 6-5: Probability
Add to to get the cumulative area of Then look for that value inside Table E.
The z value is 0.56.
Bluman, Chapter 6

34. 6.2 Applications of the Normal Distributions
The standard normal distribution curve can be used to solve a wide variety of practical problems. The only requirement is that the variable be normally or approximately normally distributed.
For all the problems presented in this chapter, you can assume that the variable is normally or approximately normally distributed.
Bluman, Chapter 6

35. Applications of the Normal Distributions
To solve problems by using the standard normal distribution, transform the original variable to a standard normal distribution variable by using the z value formula.
This formula transforms the values of the variable into standard units or z values. Once the variable is transformed, then the Procedure Table (Sec. 6.1) and Table E in Appendix C can be used to solve problems.
Bluman, Chapter 6

36. Chapter 6 Normal Distributions
Section 6-2
Example 6-6
Page #315
Bluman, Chapter 6

37. Example 6-6: Summer Spending
A survey found that women spend on average $ on beauty products during the summer months.
Assume the standard deviation is $29.44.
Find the percentage of women who spend less than $ Assume the variable is normally distributed.
Bluman, Chapter 6

38. Example 6-6: Summer Spending
Step 1: Draw the normal distribution curve.
Bluman, Chapter 6

39. Example 6-6: Summer Spending
Step 2: Find the z value corresponding to $
Step 3: Find the area to the left of z = 0.47.
Table E gives us an area of
68% of women spend less than $160.
Bluman, Chapter 6

40. Chapter 6 Normal Distributions
Section 6-2
Example 6-7a
Page #315
Bluman, Chapter 6

41. Example 6-7a: Newspaper Recycling
Each month, an American household generates an average of 28 pounds of newspaper for garbage or recycling. Assume the standard deviation is 2 pounds. If a household is selected at random, find the probability of its generating between 27 and 31 pounds per month. Assume the variable is approximately normally distributed.
Step 1: Draw the normal distribution curve.
Bluman, Chapter 6

42. Example 6-7a: Newspaper Recycling
Step 2: Find z values corresponding to 27 and 31.
Step 3: Find the area between z = -0.5 and z = 1.5.
Table E gives us an area of – = The probability is 62%.
Bluman, Chapter 6

43. Chapter 6 Normal Distributions
Section 6-2
Example 6-8
Page #317
Bluman, Chapter 6

44. Example 6-8: Coffee Consumption
Americans consume an average of 1.64 cups of coffee per day. Assume the variable is approximately normally distributed with a standard deviation of 0.24 cup.
If 500 individuals are selected, approximately how many will drink less than 1 cup of coffee per day?
Bluman, Chapter 6

45. Example 6-8: Coffee Consumption
Step 1: Draw the normal distribution curve.
Bluman, Chapter 6

46. Example 6-8: Coffee Consumption
Step 2: Find the z value for 1.
Step 3: Find the area to the left of z = – It is
Step 4: To find how many people drank less than 1 cup of coffee, multiply the sample size 500 by to get Since we are asking about people, round the answer to 2 people. Hence, approximately 2 people will drink less than 1 cup of coffee a day.
Bluman, Chapter 6

47. Chapter 6 Normal Distributions
Section 6-2
Example 6-9
Page #318
Bluman, Chapter 6

48. Example 6-9: Police Academy
To qualify for a police academy, candidates must score in the top 10% on a general abilities test. The test has a mean of 200 and a standard deviation of 20. Find the lowest possible score to qualify. Assume the test scores are normally distributed.
Step 1: Draw the normal distribution curve.
Bluman, Chapter 6

49. Example 6-8: Police Academy
Step 2: Subtract 1 – to find area to the left, Look for the closest value to that in Table E.
Step 3: Find X.
The cutoff, the lowest possible score to qualify, is 226.
Bluman, Chapter 6

50. Chapter 6 Normal Distributions
Section 6-2
Example 6-10
Page #319
Bluman, Chapter 6

51. Example 6-10: Systolic Blood Pressure
For a medical study, a researcher wishes to select people in the middle 60% of the population based on blood pressure. If the mean systolic blood pressure is 120 and the standard deviation is 8, find the upper and lower readings that would qualify people to participate in the study.
Step 1: Draw the normal distribution curve.
Bluman, Chapter 6

52. Example 6-10: Systolic Blood Pressure
Area to the left of the positive z: =
Using Table E, z  0.84.
Area to the left of the negative z: – =
Using Table E, z  –0.84.
The middle 60% of readings are between 113 and 127.
X = (8) =
X = 120 – 0.84(8) =
Bluman, Chapter 6

53. Normal Distributions
A normally shaped or bell-shaped distribution is only one of many shapes that a distribution can assume; however, it is very important since many statistical methods require that the distribution of values (shown in subsequent chapters) be normally or approximately normally shaped.
There are a number of ways statisticians check for normality. We will focus on three of them.
Bluman, Chapter 6

54. Checking for Normality
Histogram
Pearson’s Index PI of Skewness
Outliers
Other Tests
Normal Quantile Plot
Chi-Square Goodness-of-Fit Test
Kolmogorov-Smikirov Test
Lilliefors Test
Bluman, Chapter 6

55. Chapter 6 Normal Distributions
Section 6-2
Example 6-11
Page #320
Bluman, Chapter 6

56. Example 6-11: Technology Inventories
A survey of 18 high-technology firms showed the number of days’ inventory they had on hand. Determine if the data are approximately normally distributed.
Method 1: Construct a Histogram.
The histogram is approximately bell-shaped.
Bluman, Chapter 6

57. Example 6-11: Technology Inventories
Method 2: Check for Skewness.
The PI is not greater than 1 or less than –1, so it can be concluded that the distribution is not significantly skewed.
Method 3: Check for Outliers.
Five-Number Summary:
Q1 – 1.5(IQR) = 45 – 1.5(53) = –34.5
Q (IQR) = (53) = 177.5
No data below –34.5 or above 177.5, so no outliers.
Bluman, Chapter 6

58. Example 6-11: Technology Inventories
A survey of 18 high-technology firms showed the number of days’ inventory they had on hand. Determine if the data are approximately normally distributed.
Conclusion:
The histogram is approximately bell-shaped.
The data are not significantly skewed.
There are no outliers.
Thus, it can be concluded that the distribution is approximately normally distributed.
Bluman, Chapter 6

59. Chapter 6
The Normal Distribution
Section 6-4
Applications of the Normal Distribution

60. a. Greater than 700,000. b. Between 500,000 and 600,000.
Section 6-4 Exercise #3
a. Greater than 700,000.
b. Between 500,000 and 600,000.

61. a. Greater than 700,000
1.63

62. b. Between 500,000 and 600,000.

63. b. Between 500,000 and 600,000.
– 2 .36
– 0.36

64. That the senior owes at least $1000
Section 6-4 Exercise #11
The average credit card debt for college seniors is $ If the debt is normally distributed with a standard deviation of $1100, find these probabilities.
That the senior owes at least $1000
That the senior owes more than $4000
That the senior owes between
$3000 and $4000

65. a. That the senior owes at least $1000
– 2.06

66. b. That the senior owes more than $4000
0.67

67. c. That the senior owes between $3000 and $4000.
0.67
– 0.24

68. Section 6-4 Exercise #27

69. The bottom 18% means that 32% of the area is between z and 0
The bottom 18% means that 32% of the area is between z and 0. The corresponding z score will be
$18,840.48
$24,596
0.32
0.18

70. Chapter 6
The Normal Distribution
Section 6-5
The Central Limit Theorem

71. Section 6-5 Exercise #13

72. $2.00
$2.02

73. Section 6-5 Exercise #21
The average time it takes a group of adults to complete a certain achievement test is 46.2 minutes. The standard deviation is 8 minutes. Assume the variable is normally distributed.
Average time = 46.2 minutes, Standard deviation = 8 minutes, variable is normally distributed.

74. Average time = 46.2 minutes, Standard deviation = 8 minutes, variable is normally distributed.

75. 43
46.2

76. 43
46.2

77. Yes, since it is within one
standard deviation of the mean.
It is very unlikely, since the
probability would be less than 1%.

78. Section 6-5 Exercise #23
The average cholesterol of a certain brand of eggs is 215 milligrams, and the standard deviation is 15 milligrams. Assume the variable is normally distributed.

79. 220
215

80. 215
220

81. Chapter 6
The Normal Distribution
Section 6-6
The Normal Approximation to
The Binomial Distribution

82. Section 6-6 Exercise #5
Two out of five adult smokers acquired the habit by age 14. If 400 smokers are randomly selected, find the probability that 170 or more acquired the habit by
age 14.

83. 169.5
160

84. Section 6-6 Exercise #7
The percentage of Americans 25 years or older who have at least some college education is 50.9%. In a random sample of 300 Americans 25 years and older, what is the probability that more than 175 have at least some college education?

85. 175.5
152.7

86. Section 6-6 Exercise #11
Women comprise 83.3% of all elementary school teachers. In a random sample of 300 elementary school teachers, what is the probability that more than 50 are men?

87. 50.5
50.1